code: def get_model_config(
      project_path: str,
      model_name: str,
      dataset_path: str,
      category: str,
      task: str = "classification",
      export_mode: Optional[str] = None,
  ):
      model_config = get_configurable_parameters(model_name=model_name)
      model_config.project.path = project_path
      model_config.dataset.task = task
      model_config.dataset.path = dataset_path
      model_config.dataset.category = category
      model_config.trainer.fast_dev_run = True
      model_config.trainer.max_epochs = 1
      model_config.trainer.devices = 1
      model_config.trainer.accelerator = "gpu"
      model_config.optimization.export_mode = export_mode
      return model_config
  
file_path: anomalib/tests/pre_merge/utils/sweep/conftest.py
imports: from tempfile import TemporaryDirectory
  from typing import Optional, Union
  import pytest
  from omegaconf import DictConfig, ListConfig
  from pytorch_lightning import Trainer
  from anomalib.config import get_configurable_parameters
  from anomalib.data import get_datamodule
  from anomalib.models import get_model
  from anomalib.utils.callbacks import get_callbacks
label_desc: Use image node_id 1 for calling a global function with example usage: get_model_config(project_path, model_name, dataset_path, category, task, export_mode) and returns: model_config